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AI-driven Risk Management Strategies

his course offers a comprehensive exploration of how Artificial Intelligence (AI) is transforming the risk management landscape. Participants will gain a strong foundation in key AI technologies—such as machine learning, natural language processing, and expert systems—and how these tools are reshaping traditional risk approaches. Through interactive sessions, real-world examples, and a practical group exercise, delegates will learn to apply AI for predictive risk analysis, real-time monitoring, and strategic decision-making. The course also addresses critical ethical and regulatory considerations, including algorithmic bias, fairness, and privacy compliance. By the end of the programme, participants will be equipped to design and implement AI-driven risk strategies, integrate AI into governance frameworks, and prepare for emerging trends such as generative AI and quantum computing. Ideal for professionals seeking to strengthen resilience, agility, and innovation in risk management.

Course outcomes:

  • Understand foundational concepts of AI and its application in risk management.
  • Apply AI technologies for risk prediction, detection, and mitigation.
  • Leverage real-time data and AI-powered tools to enhance decision-making.
  • Recognize and address ethical risks such as bias, discrimination, and transparency challenges.
  • Ensure compliance with regulatory and ethical frameworks in deploying AI systems.
  • Develop a strategic AI risk governance framework that integrates predictive and real-time analytics.
  • Explore future trends in AI to future-proof organizational risk management practices.
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Day 1: Predictive modelling, regulation and ethical considerations

Session 1: Foundations of AI in Risk Management

  • Introduction to Artificial Intelligence (AI)
  • Overview of AI technologies: ML, NLP, Computer Vision, Expert Systems
  • Evolution from traditional to AI-driven risk management
  • Understanding AI risk governance

Session 2: Predictive Risk Management with AI

  • Implementing AI for risk prediction
  • Using AI models for market crash and cyber threat forecasting
  • Automation in monitoring and alerts

Session 3: Ethical & Regulatory Considerations

  • Ethics in AI: Bias, fairness, transparency
  • Regulatory frameworks (GDPR, AI ethics)
  • Case examples: Algorithmic bias and privacy concerns

 

Day 2: Real-time risk monitoring, reporting and measurement against risk appetite

Session 4: Real-Time Risk Monitoring

  • AI dashboards for live tracking
  • AI in crisis management and decision-support
  • Examples: Manufacturing, supply chain, cybersecurity

Session 5: Strategy & Group Exercise

  • Group activity: Develop an AI risk management strategy
  • Incorporating predictive, real-time, and ethical factors
  • Presentation and peer feedback

Session 6: Future Trends & Risk Governance

  • Exploring generative AI, quantum computing
  • AI risk governance pillars: Proactive to resilient models
  • Key takeaways and wrap-up discussion

Who should Attend?

  • Risk Management Professionals
  • Corporate Governance Officers
  • Organisational Development & Transformation Specialists
  • Line Managers, Team Leaders, and Supervisors
  • Executives and Board Members